As an important extrinsic source of mortality, harvest should select for fast reproduction and accelerated life histories. However, if vulnerability to harvest depends upon female reproductive status, patterns of selectivity could diverge and favor alternative reproductive behaviors. Here, using more than 20 years of detailed data on survival and reproduction in a hunted large carnivore population, we show that protecting females with dependent young, a widespread hunting regulation, provides a survival benefit to females providing longer maternal care. This survival gain compensates for the females' reduced reproductive output, especially at high hunting pressure, where the fitness benefit of prolonged periods of maternal care outweighs that of shorter maternal care. Our study shows that hunting regulation can indirectly promote slower life histories by modulating the fitness benefit of maternal care tactics. We provide empirical evidence that harvest regulation can induce artificial selection on female life history traits and affect demographic processes.
There is a widespread belief that women are better at selecting gifts than men; however, this claim has not been assessed on the basis of objective criteria. The current studies do exactly that and show that women do indeed make better gift selections for others, regardless of the gender of the receiver and the type of relationship between the giver and receiver. We investigate the mediating role of different aspects of interpersonal sensitivity and reveal that differences in interpersonal interest (measured with an autism questionnaire), but not differences in interpersonal reactivity, explain gender differences in gift selection quality. The current studies thus present the first objective evidence for the claim that women are better in selecting gifts for others and also give an indication of why this is the case.
- Proceedings of the National Academy of Sciences of the United States of America
- Published over 6 years ago
Domestication of wild boar (Sus scrofa) and subsequent selection have resulted in dramatic phenotypic changes in domestic pigs for a number of traits, including behavior, body composition, reproduction, and coat color. Here we have used whole-genome resequencing to reveal some of the loci that underlie phenotypic evolution in European domestic pigs. Selective sweep analyses revealed strong signatures of selection at three loci harboring quantitative trait loci that explain a considerable part of one of the most characteristic morphological changes in the domestic pig-the elongation of the back and an increased number of vertebrae. The three loci were associated with the NR6A1, PLAG1, and LCORL genes. The latter two have repeatedly been associated with loci controlling stature in other domestic animals and in humans. Most European domestic pigs are homozygous for the same haplotype at these three loci. We found an excess of derived nonsynonymous substitutions in domestic pigs, most likely reflecting both positive selection and relaxed purifying selection after domestication. Our analysis of structural variation revealed four duplications at the KIT locus that were exclusively present in white or white-spotted pigs, carrying the Dominant white, Patch, or Belt alleles. This discovery illustrates how structural changes have contributed to rapid phenotypic evolution in domestic animals and how alleles in domestic animals may evolve by the accumulation of multiple causative mutations as a response to strong directional selection.
Medicinal chemists' “intuition” is critical for success in modern drug discovery. Early in the discovery process, chemists select a subset of compounds for further research, often from many viable candidates. These decisions determine the success of a discovery campaign, and ultimately what kind of drugs are developed and marketed to the public. Surprisingly little is known about the cognitive aspects of chemists' decision-making when they prioritize compounds. We investigate 1) how and to what extent chemists simplify the problem of identifying promising compounds, 2) whether chemists agree with each other about the criteria used for such decisions, and 3) how accurately chemists report the criteria they use for these decisions. Chemists were surveyed and asked to select chemical fragments that they would be willing to develop into a lead compound from a set of ∼4,000 available fragments. Based on each chemist’s selections, computational classifiers were built to model each chemist’s selection strategy. Results suggest that chemists greatly simplified the problem, typically using only 1-2 of many possible parameters when making their selections. Although chemists tended to use the same parameters to select compounds, differing value preferences for these parameters led to an overall lack of consensus in compound selections. Moreover, what little agreement there was among the chemists was largely in what fragments were undesirable. Furthermore, chemists were often unaware of the parameters (such as compound size) which were statistically significant in their selections, and overestimated the number of parameters they employed. A critical evaluation of the problem space faced by medicinal chemists and cognitive models of categorization were especially useful in understanding the low consensus between chemists.
Large numbers of inbred laboratory rat strains have been developed for a range of complex disease phenotypes. To gain insights into the evolutionary pressures underlying selection for these phenotypes, we sequenced the genomes of 27 rat strains, including 11 models of hypertension, diabetes, and insulin resistance, along with their respective control strains. Altogether, we identified more than 13 million single-nucleotide variants, indels, and structural variants across these rat strains. Analysis of strain-specific selective sweeps and gene clusters implicated genes and pathways involved in cation transport, angiotensin production, and regulators of oxidative stress in the development of cardiovascular disease phenotypes in rats. Many of the rat loci that we identified overlap with previously mapped loci for related traits in humans, indicating the presence of shared pathways underlying these phenotypes in rats and humans. These data represent a step change in resources available for evolutionary analysis of complex traits in disease models. PAPERCLIP:
BACKGROUND: Kin selection is a driving force in the evolution of mammalian social complexity. Recognition of paternal kin using vocalizations occurs in taxa with cohesive, complex social groups. This is the first investigation of paternal kin recognition via vocalizations in a small-brained, solitary foraging mammal, the grey mouse lemur (Microcebus murinus), a frequent model for ancestral primates. We analyzed the high frequency/ultrasonic male advertisement (courtship) call and alarm call. RESULTS: Multi-parametric analyses of the calls' acoustic parameters and discriminant function analyses showed that advertisement calls, but not alarm calls, contain patrilineal signatures. Playback experiments controlling for familiarity showed that females paid more attention to advertisement calls from unrelated males than from their fathers. Reactions to alarm calls from unrelated males and fathers did not differ. CONCLUSIONS: 1) Findings provide the first evidence of paternal kin recognition via vocalizations in a small-brained, solitarily foraging mammal. 2) High predation, small body size, and dispersed social systems may select for acoustic paternal kin recognition in the high frequency/ultrasonic ranges, thus limiting risks of inbreeding and eavesdropping by predators or conspecific competitors. 3) Paternal kin recognition via vocalizations in mammals is not dependent upon a large brain and high social complexity, but may already have been an integral part of the dispersed social networks from which more complex, kin-based sociality emerged.
A progressive increase in the incidence of thyroid cancer (TC) has been reported over the last few decades. This either reflects the increased number of newly discovered and accurately selected thyroid nodules with more sensitive technologies and a relative more potent carcinogenic effect of pathogenetic factors in malignant, but not benign nodules. This observational time-trend study addresses this issue by analysing the proportion of TC within 8411 consecutive thyroid nodule (TN) patients evaluated in Pisa by the same pathology Department and individual clinician over a four-decade period. From 1972 to 1979 surgery was used to detect TC among the TN patients: 1140 TN patients were operated on and 35 cancers were detected (3.1% of all the TN patients). Subsequently, needle aspiration techniques were used to select TN for surgery. From 1980 to 1992, 5403 TN patients were examined, 483 were selected for surgery, and 150 cancers were found (2.8% of all the TN patients). From 1993 to 2010, 1568 TN patients were examined, 143 were selected for surgery, and 46 cancers were found (2.9% of all the TN patients). Therefore, in the University Hospital of Pisa, and independent of preoperative TN selection protocols, these proportions of TN eventually found to harbor TC remained statistically unchanged over 40 years (p = 0.810). This finding suggests that pathogenic risk factors and more sensitive diagnostic technologies did not differentially affect the incidence of TN and TC.
How wolves were first domesticated is unknown. One hypothesis suggests that wolves underwent a process of self-domestication by tolerating human presence and taking advantage of scavenging possibilities. The puppy-like physical and behavioural traits seen in dogs are thought to have evolved later, as a byproduct of selection against aggression. Using speed of selection from rehoming shelters as a proxy for artificial selection, we tested whether paedomorphic features give dogs a selective advantage in their current environment. Dogs who exhibited facial expressions that enhance their neonatal appearance were preferentially selected by humans. Thus, early domestication of wolves may have occurred not only as wolf populations became tamer, but also as they exploited human preferences for paedomorphic characteristics. These findings, therefore, add to our understanding of early dog domestication as a complex co-evolutionary process.
One of the most intriguing questions in evolution is how organisms exhibit suitable phenotypic variation to rapidly adapt in novel selective environments. Such variability is crucial for evolvability, but poorly understood. In particular, how can natural selection favour developmental organisations that facilitate adaptive evolution in previously unseen environments? Such a capacity suggests foresight that is incompatible with the short-sighted concept of natural selection. A potential resolution is provided by the idea that evolution may discover and exploit information not only about the particular phenotypes selected in the past, but their underlying structural regularities: new phenotypes, with the same underlying regularities, but novel particulars, may then be useful in new environments. If true, we still need to understand the conditions in which natural selection will discover such deep regularities rather than exploiting ‘quick fixes’ (i.e., fixes that provide adaptive phenotypes in the short term, but limit future evolvability). Here we argue that the ability of evolution to discover such regularities is formally analogous to learning principles, familiar in humans and machines, that enable generalisation from past experience. Conversely, natural selection that fails to enhance evolvability is directly analogous to the learning problem of over-fitting and the subsequent failure to generalise. We support the conclusion that evolving systems and learning systems are different instantiations of the same algorithmic principles by showing that existing results from the learning domain can be transferred to the evolution domain. Specifically, we show that conditions that alleviate over-fitting in learning systems successfully predict which biological conditions (e.g., environmental variation, regularity, noise or a pressure for developmental simplicity) enhance evolvability. This equivalence provides access to a well-developed theoretical framework from learning theory that enables a characterisation of the general conditions for the evolution of evolvability.
It has become increasingly clear that low levels of antibiotics present in many environments can select for resistant bacteria, yet the evolutionary pathways for resistance development during exposure to low amounts of antibiotics remain poorly defined. Here we show that Salmonella enterica exposed to sub-MIC levels of streptomycin evolved high-level resistance via novel mechanisms that are different from those observed during lethal selections. During lethal selection only rpsL mutations are found, whereas at sub-MIC selection resistance is generated by several small-effect resistance mutations that combined confer high-level resistance via three different mechanisms: (i) alteration of the ribosomal RNA target (gidB mutations), (ii) reduction in aminoglycoside uptake (cyoB, nuoG, and trkH mutations), and (iii) induction of the aminoglycoside-modifying enzyme AadA (znuA mutations). These results demonstrate how the strength of the selective pressure influences evolutionary trajectories and that even weak selective pressures can cause evolution of high-level resistance.